Hyperparameter Optimization for Large-Scale Remote Sensing Image Analysis Tasks: A Case Study Based on Permafrost Landform Detection Using Deep Learning

Hyperparameter Optimization for Large-Scale Remote Sensing Image Analysis Tasks: A Case Study Based on Permafrost Landform Detection Using Deep Learning

Climate change pressure on the Arctic permafrost is rising alarmingly, creating a decisive need to produce Pan-Arctic scale permafrost landform and thaw disturbance information from remote sensing (RS) data. Very high spatial resolution (VHSR) satellite images can be utilized to detect ice-wedge pol...

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Bibliographic Details
Main Authors: Amal S. Perera, Chandi Witharana, Elias Manos, Anna K. Liljedahl
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Remote sensing
deep learning
hyperparameter optimization
terrain mapping
convolutional neural networks
climate change
Online Access:https://ieeexplore.ieee.org/document/10474435/

Internet

https://ieeexplore.ieee.org/document/10474435/

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